title: Roboneuron: a simple and robust real-time analog spike simulator and calibrator.
abstract: BACKGROUND
  Modern computerized spike recording systems are increasingly powerful and sophisticated. However, this increases the importance of performing validation by recording signals from a system with a known input-output relationship.
  
  
  METHODS
  We present here a simple and robust analog circuit that uses a minimum number of commonly available components to simulate two independently spiking neurons. The two neurons generate asynchronous overlapping spikes. These can be independently set to spike at either a constant rate, or at a rate set by an external control voltage.
  
  
  RESULTS
  The circuit is simple enough to easily assemble by hand, however, standard files for ordering commercial printed circuit boards are also supplied. Several units were built by different people, using both hand-assembly and commercially manufactured printed circuit boards: all worked well. The circuit is robust with respect to supply voltages and component values.
  
  
  METHODS
  Existing analog circuits tend to be complex, hard to assemble, and use hard-to-find components. Digital simulators typically require specific development systems that have steep learning curves and are likely to change radically or become unavailable very quickly. This system has been optimized to be robust, simple, and use only commonly available components.
  
  
  CONCLUSIONS
  When validating a system there could be an advantage to using a calibrator that is robust, whose input-output relationship is simple, and whose design is stable over time.
authors.affiliation: Department of Neuroscience, Vision Science Research Center, University of Alabama at Birmingham (UAB), Birmingham, AL 35294, USA.
authors.forename: Tyler
authors.initials: T
authors.lastname: Dickerhoff
authors.forename: Abidin
authors.initials: A
authors.lastname: Yildirim
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Gawne
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D002138:Calibration; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*
keywords: Calibrator; Circuit; Neuron; Spike sorter; Spiking model